The third approach we consider is atlas-based label propagation. Label propagation using multiple atlases have been shown to yield state-of-the-art results on many segmentation problems [1]}. A common procedure in multi-atlas methods is to use non-rigid registration to align the atlases with the image to be segmented and then perform label fusion strategies to obtain predictions for each image point. Although, multi-atlas methods based on registration are not strictly voxel-wise classifiers as they operate on the whole image during registration, the final stage of label fusion can be considered as a voxel-wise classification step. Here, we make use of an approach that has been originally developed in the context of segmentation of cardiac MRI [2]}Code available at https://github.com/baiwenjia/CIMAS. For the purpose of RCA, however, there is only a single atlas and thus no label fusion is required. Using single atlas label propagation then boils down to making use of an efficient non-rigid registration technique as the one described in [2]}. For RCA, the single atlas then corresponds to the image and its predicted segmentation for which we want to estimate the segmentation quality. We use the same configuration for image registration as in [2]} and refer to this work for further details.
